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ICML
2007
IEEE
14 years 6 months ago
Discriminant kernel and regularization parameter learning via semidefinite programming
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
Jieping Ye, Jianhui Chen, Shuiwang Ji
IJON
2010
178views more  IJON 2010»
13 years 3 months ago
An empirical study of two typical locality preserving linear discriminant analysis methods
: Laplacian Linear Discriminant Analysis (LapLDA) and Semi-supervised Discriminant Analysis (SDA) are two recently proposed LDA methods. They are developed independently with the a...
Lishan Qiao, Limei Zhang, Songcan Chen
ICPR
2008
IEEE
13 years 11 months ago
Boosting performance for 2D Linear Discriminant Analysis via regression
Two Dimensional Linear Discriminant Analysis (2DLDA) has received much interest in recent years. However, 2DLDA could make pairwise distances between any two classes become signiï...
Nam Nguyen, Wanquan Liu, Svetha Venkatesh
PR
2008
161views more  PR 2008»
13 years 5 months ago
A study on three linear discriminant analysis based methods in small sample size problem
In this paper, we make a study on three Linear Discriminant Analysis (LDA) based methods: Regularized Discriminant Analysis (RDA), Discriminant Common Vectors (DCV) and Maximal Ma...
Jun Liu, Songcan Chen, Xiaoyang Tan
IBPRIA
2005
Springer
13 years 11 months ago
Dynamic Texture Recognition Using Normal Flow and Texture Regularity
The processing, description and recognition of dynamic (time-varying) textures are new exciting areas of texture analysis. Many real-world textures are dynamic textures whose retri...
Renaud Péteri, Dmitry Chetverikov